ISSN 1000-1239 CN 11-1777/TP

• 信息安全 •

### 适用于智能环境的高效安全云辅助模式匹配协议

1. (山东师范大学信息科学与工程学院 济南 250358) (wxc@sdnu.edu.cn)
• 出版日期: 2019-11-12
• 基金资助:
中国博士后科学基金项目(2018M632712)；国家自然科学基金青年科学基金项目(61802235)；山东省重点研发计划(2018GGX101037)；山东省科技重大创新工程项目(2018CXGC0702)

### Efficient and Secure Cloud-Assisted Pattern Matching Protocol for Intelligent Environment

Wei Xiaochao, Xu Lin, Zheng Zhihua, Wang Hao

1. (School of Information Science and Engineering, Shandong Normal University, Jinan 250358)
• Online: 2019-11-12

Abstract: The intelligent environment built by machine learning, artificial intelligence, Internet of things is changing the way people live, work and think. The way of data storage and processing in intelligent environment is changing constantly, where security and efficiency are two important factors. In terms of security, privacy must be guaranteed during the sharing and analysis of data. In addition, many devices with limited resources exist in the intelligent environment, whose feasibility is directly influenced by how to design suitable algorithms or protocols. Based on the above two requirements, this paper studies the problem of secure pattern matching for intelligent environment. In the traditional secure pattern matching protocol, the pattern holder needs to compute lots of public-key operations，which is unsuitable for a resource-limited device such as a mobile phone. In this paper, we formalize the functionality of the secure pattern matching protocol under the two-cloud-assisted secure two-party computation model for the first time, and construct an efficient protocol via oblivious transfer (OT). The protocol is secure in semi-honest adversary model, assuming that no collusion exists between the cloud servers and the participants. The protocol requires 4 rounds, and the pattern holder performs only a small number of XOR operations, and the complex OT protocols are mainly executed between the database and the cloud servers. Furthermore, the OT extension technology can reduce the number of all OT protocols from O(nm) to O(k), where n and m are the input lengths of the two participants, and k is the number of base OT in OT extension protocol, which is much smaller than nm.